ReVivo Medical, LLC has developed the next generation of spinal fusion implants to help surgeons and hospitals achieve the goals of the Affordable Care Act. ReVivo's spinal implants are the first to leverage the basic science of bone formation to reduce time to fusion, while also diminishing complication rates, decreasing operating room time, and lowering overall cost. ReVivo Medical's solution to improving spine fusion is a suite of continuously load-sharing elastically deformable spinal implants. By design, the stiffness of ReVivo's implants allows for micro-deformation under physiologic loading. This promotes continuous load-sharing which we expect will lead to more rapid bony fusion. The objective of this Phase I proposal is to demonstrate the efficacy of our elastically deformable, continuously load-sharing spinal implants to promote a faster and higher quality spinal fusion relative to existing plates. In the proposed Phase I work, we will establish that continuous load-sharing through controlled micro-motion will improve the rate and quality of interbody fusion in vivo. In a clinically relevant in vivo large animal model, we will correlate implant design to the clinically relevant metrics of subsidence, screw backout, and rate and quality of fusion. We hypothesize that an elastically deformable, continuously load-sharing implant will reduce subsidence, reduce screw backout, and enhance the rate and quality of bony fusion relative to existing static and dynamic plates. We will perform an anterior cervical discectomy and fusion on 18 goats with animals grouped to receive either anterior (a) static plates, (b) dynamic plates, or (c) ReVivo Medical's elastically deformable plates. Over a 14 week period, the progression of fusion will be monitored biweekly by plain x-rays and by CT scans at 6 and 12 weeks. Post mortem, excised spines will be CT scanned and analyzed histologically to determine quality of fusion. Serial x-rays will be analyzed for evidence of subsidence, screw backout, implant migration, and extent of fusion. Data will be compared across treatment groups and across time points to assess differences.